Cancer is a complex and heterogeneous disease, not only at a genetic and biochemical
level, but also at a tissue, organism, and population level. Multiple data streams, from …

Rather than a strictly formalized methodological framework, we here describe systems
biology as a flexible approach in which the modelling strategy used depends on a trade-off …

Cancer research has focused on the identification of molecular differences between
cancerous and healthy cells. The emerging picture is overwhelmingly complex. Molecules …

An important challenge facing the field is how better to translate in vitro discoveries to the
clinic. Computational systems biology approaches that use omic data to predict biology …

In order to understand how a cancer cell is functionally different from a normal cell it is
necessary to assess the complex network of pathways involving gene regulation, signaling …

Systems biology analyses in cancer are rapidly changing from merely descriptive efforts in
the high-throughput experimental works and overtly technical, calculation-centered studies …

Systems biology uses systems of mathematical rules and formulas to study complex
biological phenomena. In cancer research there are three distinct threads in systems biology …

Current cancer therapies target a limited set of tumor features, rather than considering the
tumor as a whole. Systems biology aims to reveal therapeutic targets associated with a …

The unprecedented amount of data produced with high-throughput experimentation forces
biologists to employ mathematical representation and computation to glean meaningful …

The transformation of normal cells into cancer cells and maintenance of the malignant state
and phenotypes are associated with genetic and epigenetic deregulations, altered cellular …